function [c,ceq] = nonlcon105(x,feedback,settings)
% For all predicted time points, the variance should be smaller than the
% set point of var(R2), thus
%   c(i) = varR2-varR2_set <= 0
% 

P = settings.P;
c = zeros(1,P);

State = model_setState(feedback);
for i = 1:P
    State= model(x(i),State,settings.dt);
    c(i) = State.varR2-settings.varR2_set;
end

ceq = [];